Full‑stack developer

Python • C++ • JS/TS

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Featured Projects

Full-stack

Developer

AI/Cloud

Specialist

Skills

Core Stack

PythonTypeScriptC#

Frontend

ReactNext.jsTypeScriptReact NativeTailwind CSS

Backend

Node.jsExpressFastAPIRESTWeb APIs

AI/LLM

RAGLLM Integration(LangChain, OpenAI, Hugging Face)Vector Database(Milvus)RF(PPO/DQN),ML(Random Forest, Decision Tree)

DevOps & Cloud

AWS(EC2, S3, RDS,EKS)DockerGitHub ActionsVercelGit

Database

PostgreSQLMySQLMongoDBRedis

Featured Projects

Highlighted work

ReadySetHire

Full-Stack Developer

AI-Powered Hiring Platform

Live Demo GitHub

A production-ready SaaS platform that streamlines the hiring workflow with AI-powered resume screening and job search aggregation. Built with a focus on scalability, user experience, and automated testing. Implements subscription-based monetization and supports multiple languages for global reach.

Impact & Results

▸Automated resume screening with AI-powered scoring algorithms
▸Supports concurrent job search across multiple platforms
▸Deployed on AWS ECS with 99%+ uptime and auto-scaling
▸Comprehensive test coverage with Jest and CI/CD automation

Tech Stack

TypeScriptReactExpress.jsDockerAWS ECSJestGitHub Actions

Key Features

✓AI resume scoring with multiple accuracy tiers
✓Real-time job search aggregation
✓Team collaboration with shared evaluations
✓Subscription payment system (Trial/Premium)
✓Multilingual UI (EN/CN)

Landing Page

Subscription Plans

Job Search & Details

RF-for-shapez

Solo Developer

Reinforcement Learning Game AI

GitHub

An end-to-end AI automation project demonstrating expertise in game development, machine learning, and system integration. Developed a complete game engine in C++/Qt, then trained a reinforcement learning agent to autonomously master the game. Showcases advanced skills in inter-process communication, GUI development, and practical RL applications.

Impact & Results

▸Successfully trained PPO agent to play complex strategy game
▸Implemented robust IPC via shared memory for real-time data transfer
▸Built intuitive PyQt5 training interface for model management
▸Achieved automated gameplay through computer vision and UI automation

Tech Stack

C++QtPythonPPO (Reinforcement Learning)PyTorchStable-Baselines3PyQt5PyAutoGUI

Key Features

✓Full game implementation in C++ with Qt framework
✓PPO reinforcement learning with action masking
✓Shared memory IPC for game state reading
✓PyQt5 training GUI with model selection
✓Automated gameplay via PyAutoGUI screen matching
✓Custom Gymnasium environment integration

Game Interface

Training Interface

Quant Trading System

Backend & Infrastructure Developer

Cryptocurrency Algorithmic Trading Platform

Live Demo GitHub

A production-grade microservices platform for algorithmic cryptocurrency trading. Architected for high reliability and real-time performance with event-driven communication, time-series data optimization, and comprehensive risk management. Demonstrates expertise in distributed systems, cloud infrastructure, and financial technology.

Impact & Results

▸Processes real-time market data from multiple exchanges via WebSocket
▸Stores and analyzes time-series data with optimized TimescaleDB queries
▸Event-driven architecture enables low-latency order execution
▸Infrastructure as Code with Terraform ensures reproducible deployments

Tech Stack

PythonCCXT ProTimescaleDBRedisWebSocketPostgreSQLDockerAWS ECSTerraformMkDocs

Key Features

✓Real-time market data aggregation from exchanges
✓Time-series storage with TimescaleDB for ticker data
✓Event-driven microservices architecture (pub/sub)
✓Feature calculation & rolling window analysis
✓Automated order management with risk controls
✓Asset pool rebalancing & portfolio management

About

Professional Summary

Full-stack developer with expertise in building production-ready web applications, distributed systems, and AI-powered solutions. Specialized in microservices architecture, cloud infrastructure (AWS), and modern JavaScript/TypeScript ecosystems. Experienced in delivering scalable SaaS platforms, implementing reinforcement learning systems, and designing event-driven architectures. Strong advocate for clean code, comprehensive testing, and DevOps best practices.

Technical Expertise

Backend & Infrastructure

• Microservices architecture with Docker & AWS ECS
• RESTful APIs with Node.js/Express & Python/FastAPI
• Infrastructure as Code with Terraform
• Event-driven systems with Redis pub/sub

Frontend & Full-Stack

• Modern React with Next.js & TypeScript
• State management & real-time data handling
• Responsive UI with Tailwind CSS
• End-to-end testing with Jest

AI & Machine Learning

• LLM integration (OpenAI, LangChain, RAG)
• Reinforcement Learning (PPO, DQN)
• Vector databases (Milvus) for semantic search
• PyTorch & Stable-Baselines3

Data & DevOps

• Time-series data with TimescaleDB/PostgreSQL
• CI/CD pipelines with GitHub Actions
• Real-time data processing with WebSockets
• Cloud deployment & monitoring (AWS)

Project Highlights

AI-Powered SaaS Platform

Built a full-stack hiring platform with AI resume screening, payment integration, and multilingual support. Deployed on AWS ECS with Docker containerization and automated CI/CD pipelines.

Quantitative Trading System

Architected a microservices-based trading platform with real-time market data aggregation, event-driven communication, and automated order execution. Managed infrastructure with Terraform.

Reinforcement Learning Application

Developed a complete game in C++/Qt and trained an AI agent using PPO reinforcement learning. Implemented cross-process communication and automated UI interaction systems.

Contact

Email GitHub